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well_show_records
Read-only

Put a table of records IN FRONT OF THE USER. Use it when the user asked to SEE rows — "show me my invoices", "list my companies", "which suppliers have no category" — and when the answer you owe them IS the table.

The table is ALWAYS the root's display view in the Well web app's column order, trimmed on the widest roots to what fits a chat-width table. You never choose columns for presentation: omit fields and the right ones render.

⚠️ FOR A READ THAT IS YOURS RATHER THAN THEIRS, CALL well_query_records INSTEAD. Same arguments, same rows, no table. Every gate, count, freshness check and intermediate read belongs there — this tool renders on every call, so using it for an internal check drops a table into a conversation about something else.

⚠️ DO NOT NARRATE THE TABLE. The card already shows these rows; restating them as markdown gives the user the table and a duplicate list under it. Two things the table cannot say for itself belong in your text: totalCount when it exceeds what is displayed ("showing the 50 most recently updated of 214"), and the records_url link for everything the card truncates.

⚠️ ONE CARD PER TURN. A turn draws at most one table, and never a table beside a card that is waiting for a click.

ROOTS (read-only — all 33): companies, people, connectors, invoices, documents, transactions, accounts, payment_means, workspace_connectors, memberships, cards, checks, ledger_accounts, journals, journal_entries, tax_rates, exchange_rates, invoice_transactions, categories, account_balances, tasks, workspaces, invoice_payment_means, chat_conversations, blueprint_runs, workspace_connector_sync_logs, media, emails, phones, web_links, locations, invoice_items, billing_events (The accounting graph — ledger_accounts, journals, journal_entries — and balances/rates are read-only projections owned by the sync/posting pipelines; query them for financial context, you cannot create/update them here. Sub-resources like emails/phones/locations are usually richer when read via their parent company/person.)

CATEGORY CATALOGS: "categories" holds two independent taxonomies, separated by category_type. Always filter on it — an unfiltered read mixes them:

  • whereClause: { category_type: { _eq: "company" } } is the COMPANY-CATEGORY catalog: the industry labels a counterparty carries, and the ids well_update_company({ category_ids }) accepts. There is no curated allowlist — the labels are minted during enrichment — so read them here rather than inventing a taxonomy.

  • whereClause: { category_type: { _eq: "transaction" } } is the management/transaction taxonomy.

CONNECTED TOOLS: do NOT use this tool to show the user what they have connected — call well_list_connectors instead. It owns that job: connection status, and an install link for anything not connected yet. Query root "workspace_connectors" here only for genuine RECORD-level needs — reading sync timestamps, filtering connections, joining them with other roots. ("connectors" is the installable catalog; "workspace_connector_sync_logs" is per-sync history.)

Well already syncs the providers' data into the roots above — invoices, transactions, accounts, the accounting graph. ALWAYS read it from here. well_invoke_connector_tool and a provider's own tools are for an ACTION the user explicitly asked to take on that provider (e.g. "create this record in Attio"), never a way to fetch data Well already holds.

FILTERING (whereClause):

  • Uses Hasura-style operators on field names.

  • Safe operators (work on ALL field types): _eq, _neq, _in, _nin, _is_null

  • Numeric/date only: _gt, _gte, _lt, _lte

  • Text only: _like, _ilike

  • When unsure of a field's type, prefer _eq or _in (they always work).

  • Combine with _and, _or, _not

  • For relationship fields, use nested syntax: { "issuer": { "company_id": { "_eq": "" } } }

  • NEVER select the workspace's OWN records by matching a company name. One legal entity appears under several labels — a registered name, a trade name, a bank-issued label — so a name filter silently drops rows and the total reads as complete. On the invoices root, pass partyScope instead: it resolves the workspace's own side on the server, so this query needs no id lookup and no extra call. Call well_get_own_company for the id only when a root has no partyScope and you must filter on issuer_pk / receiver_pk or the nested company_id yourself.

  • Match a counterparty by id too whenever you have one. Reach for _ilike on a name only to DISCOVER candidates to show the user, never to compute a figure you will report. Examples: { "status": { "_eq": "unpaid" } } { "grand_total": { "_gt": 1000 } } { "local_currency": { "_eq": "EUR" } } { "_and": [{ "status": { "_eq": "unpaid" } }, { "grand_total": { "_gte": 500 } }] } { "issuer": { "company_id": { "_eq": "" } } }

SORTING (orderBy):

  • Sort by any field: { field: "grand_total", direction: "desc" }

  • Default sort is by primary key ascending.

⚠️ RULES:

  • Omit fields to show the user a table — that is what renders the root's own columns

  • fields is ADDITIVE and for values YOU need to reason about: it widens the payload you read and never reorders or trims the columns the user sees

  • Field paths from schema: "invoices.issuer.name" → ["invoices", "issuer", "name"]

  • Default 50 records per request, max 500.

EXAMPLE - show the user their invoices (no fields, ever): well_show_records({ root: "invoices", limit: 50 })

ONE CALL IS THE ANSWER — do not walk the root: Every response carries totalCount (ALL matches, not just this page) and records_url (the full web-app table, with your filter and sort already applied). So a request to see a record type is ONE call: the user gets a table of the first page, the count tells them how many there are, and the link takes them to the rest. "Show me all my invoices" is answered by one call plus the link — NOT by fetching 483 rows into this conversation.

  • A non-null nextCursor is NOT a to-do. It means more rows exist, which totalCount already told you and the link already covers.

  • Never paginate to compute a total, count, average or breakdown: aggregate over the filtered set instead. Summing a paginated sample produces a wrong number.

  • Never paginate to "be thorough". Large roots will exhaust the output limit mid-walk, and the user ends up with nothing legible.

  • Paginate ONLY for per-row work over every match that no aggregate can express, and tell the user the cost before starting. Then: pass the returned nextCursor as cursor; nextCursor: null is the last page.

Returns { rows, totalCount, nextCursor, success }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rootYesThe entity type to query — any of the 33 read-only roots (companies, people, connectors, invoices, documents, transactions, accounts, payment_means, workspace_connectors, memberships, cards, checks, ledger_accounts, journals, journal_entries, tax_rates, exchange_rates, invoice_transactions, categories, account_balances, tasks, workspaces, invoice_payment_means, chat_conversations, blueprint_runs, workspace_connector_sync_logs, media, emails, phones, web_links, locations, invoice_items, billing_events). Call well_get_schema(root) first to discover fields.
limitNoMax records to return (default 50, max 500)
cursorNoOpaque cursor for the next page. Omit for the first page, then pass nextCursor from the previous response.
fieldsNoEXTRA field paths to add to the root's display view, for values you need to reason about. Each path is an array whose first segment is the root's table name — use the paths well_get_schema(root) returns verbatim, which is the root name for every root except people (whose table is peoples); a path opening with any other segment is dropped. Additive only: they widen the payload you receive, and the root's own display projection (the columns the Well web app shows, and the ones a table drawn from this query carries) stays what it is no matter what you pass here. A scalar a composite renders comes back AS that composite — asking for grand_total gets you composite_total_amount_currency, with grand_total inside it — so read `columns` for what was actually materialized. Omit unless you need a value the display view does not carry.
orderByNoSort results by a field. Example: { field: "grand_total", direction: "desc" }
allFieldsNoIf true, automatically fetches all scalar fields from schema. No need to specify fields.
partyScopeNoWhich side of an invoice the workspace itself occupies, resolved from its own company rather than a party name. `invoices` root only. "purchase" = the workspace owes it (payables); "sales" = the workspace is owed (receivables); "intra_self" = both parties are companies the workspace owns; "unattributed" = Well cannot place it on either side. The four partition every invoice, so report the "unattributed" count beside any payable total rather than dropping it — an unattributed invoice may still be owed. Prefer this over hand-writing an issuer/receiver filter.
whereClauseNoHasura-style filter object. Operators: _eq, _neq, _gt, _gte, _lt, _lte, _like, _ilike, _in, _nin, _is_null. Example: { "status": { "_eq": "unpaid" } }
workspace_idNoTarget workspace. Omit to query every authorized workspace at once; each row comes back tagged with the workspace it belongs to.
conversation_idNoThe conversation id returned by the previous Well result, in its meta under well/conversation_id, in its structuredContent, or in its JSON text block. Pass it back on every call in the same conversation, including a call a card makes, so the chosen workspace and the earlier answers still apply. It decides the conversation on its own: nothing the host states about the session replaces it. Omit it only on the first call of a conversation.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYesQuery results
errorNo
columnsNoThe materialized columns in display order, with each composite substituted in place of the source fields it consumed. A row object's key order does not preserve this — the flattener appends reconstructed composites last — so a UI that wants the web app's column order must read it from here.
successYes
returnedYesNumber of rows returned
columnMetaNoPer-column field meaning, keyed by the same column paths as the rows. `context` = what the field means; `enrichment` = how the value is sourced (e.g. Bank sync, AI extraction). Only documented columns appear. Read this to interpret the returned values.
nextCursorNoCursor for the next page. null means last page.
totalCountYesTotal matching records
records_urlNoLogin-gated deep link to the FULL web-app records table for this root (real DataTable: composites, inline editing, resize/pin), carrying this call's `whereClause` and `orderBy` so it opens on the same rows. Hand it to the user for everything past this page — it is the answer to 'show me all of them', not pagination. Null when no workspace is in context or no web page serves the root.
conversation_idNoThe conversation this result belongs to. Pass it back as the conversation_id argument on every later Well call in the same conversation.
conversation_id_noteNoPresent only when the server opened a fresh lane, stating that no choice recorded earlier was read.
conversation_id_sourceNoWhere the conversation id came from: the host's own request meta, the caller's argument, or a fresh lane the server opened.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • addedInput schema / properties / conversation_id
      Added value: +{
      +  "description": "The conversation id returned by the previous Well result, in its meta under well/conversation_id, in its structuredContent, or in its JSON text block. Pass it back on every call in the same conversation, including a call a card makes, so the chosen workspace and the earlier answers still apply. It decides the conversation on its own: nothing the host states about the session replaces it. Omit it only on the first call of a conversation.",
      +  "type": "string"
      +}
    • addedOutput schema / properties / conversation_id
      Added value: +{
      +  "description": "The conversation this result belongs to. Pass it back as the conversation_id argument on every later Well call in the same conversation.",
      +  "type": "string"
      +}
    • addedOutput schema / properties / conversation_id_note
      Added value: +{
      +  "description": "Present only when the server opened a fresh lane, stating that no choice recorded earlier was read.",
      +  "type": "string"
      +}
    • addedOutput schema / properties / conversation_id_source
      Added value: +{
      +  "description": "Where the conversation id came from: the host's own request meta, the caller's argument, or a fresh lane the server opened.",
      +  "enum": [
      +    "host_meta",
      +    "argument",
      +    "minted"
      +  ],
      +  "type": "string"
      +}
  2. Added

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint and destructiveHint annotations, the description discloses that the tool renders a table on every call, uses the app's display projection, treats fields as additive, allows at most one card per turn, and returns totalCount/records_url. It also warns against narrating the table and against paginating for aggregates — behavioral context the annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long and not telegraphic, but it is front-loaded with the core purpose, uses bold warnings and clear section headers, and almost every sentence carries a decision-relevant rule. It earns its length for a 10-parameter rendering tool, though some details are restated from the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers the full 33-root set, filtering and sorting semantics, the one-call-and-link pagination model, category catalogs, connected-tool boundaries, and the return shape. Given the rich input schema and output schema, nothing an agent needs to call this tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100%, the description adds substantial meaning beyond the schema: operator safety rules, nested relationship syntax, the partyScope guidance for avoiding name-based filtering traps, and the precise semantics of fields as additive rather than column-selecting. It also ties cursor to nextCursor and specifies when pagination is actually appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific behavior ('Put a table of records IN FRONT OF THE USER') and defines exactly when it applies ('when the user asked to SEE rows'). It explicitly names the sibling it is not — well_query_records — and the tool that owns connector display, well_list_connectors, so an agent can select it unambiguously.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use guidance with quoted user utterances and explicit when-not-to-use boundaries: internal reads go to well_query_records, connector status goes to well_list_connectors, and provider-side actions go to well_invoke_connector_tool. The description even separates category catalogs and partyScope behavior, leaving little ambiguity about which tool owns which job.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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